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Dimensioning the server

 A recommended Stand-alone Verba Speech Analytics Server Configuration:

 4GB RAM + 2GB / language model

 2 vCPU + 1 vCPU for every 200 hours of calls transcribed in 24 hours, scaling up to 16 vCPUs

Individual results may vary due the talk time in recordings, the storage codec and the language model used.

Storage requirement

The transcription only works when the media is stored on SMB storages. If the media has to be stored on a WORM or non-SMB storage, the files should be hosted temporarily on SMB and moved to the final storage target after transcription.

Server Roles

The Verba Speech Analytics Service can be enabled on the following server roles:

  • Speech Analytics Server
  • Media Repository Server

Do not enable the service on any other server role. If the service is enabled on the Media Repository Server, the service has to be configured to limit the number of simultaneous transcription processes to 1 (Speech Analytics / Transcription / Task Processing Threads Count), this will use 1 core for transcription.

The service may be enabled on multiple servers, in this case, the system will automatically handle the load balancing between servers.


Step 1 - Copy the language model file to C:\Program Files\Verba\resources\transcription\eliza

Step 2 - In the Verba Web Interface go to System > Servers > Select your Server  > Click on the Service Activation tab.
Step 3 - Activate the Verba Speech Analytics Service by clicking on the  icon.

Step 4 - Go to System > Servers > Select your Server  > Click on the Service Activation tab
Step 5 - Start the Verba Speech Analytics Service by clicking on the  icon.

For additional languages, only Step 1 needs to be repeated for the additional languages. The service will detect the new language model within 30 minutes, or you can force the detection by restarting the service. 

Creating a Data Processor

Step 1 - In the Verba Web Interface go to Data > Data Processors  

Step 2 - In the top right corner click 'Add new Data Processor' 

Step 3 - Name the Data Processor 

Step 4 - Select the Speech Transcription for Type 

Step 5 - Select Eliza for Engine  

Step 6 - Click 'Save' to save your Data Processor 

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